Computing systems often include one or more host computers (“hosts”) for processing data and running application programs, direct access storage devices (DASDs) for storing data, and a storage controller for controlling the transfer of data between the hosts and the DASD. In addition to storing actual data, also known as user or customer data, the control unit often maintains metadata which provides information on tracks or blocks of data in the DASD or in a cache of the storage controller. The storage controller processes the metadata during certain operations on the actual data represented by the metadata to improve the speed and efficiency of those requested operations.
There are numerous types of metadata, such as summary information, partial-copy information, historical information, copy services information, and log structured array information. Summary information summarizes the customer data, including information on the format of a block or track of customer data, such as a count-key-data (CKD) track. In this way, information on the actual customer data that would otherwise have to be gleaned from the customer data itself in a time consuming process is readily available. Partial copy information contains a copy of a portion of the actual customer data to improve destage performance. Historical information records historical usage of the customer data. Historical data may be used to predict future use of the user or customer data. Copy services information contains bit maps that indicate tracks of the customer data that were modified and not yet copied to a secondary site. The log structured array (LSA) information maintains an ISA directory and related data to manage the ISA.
Typically, during initialization of the DASD, metadata is copied from the DASD to the storage controller. As the size of a metadata track and the types of metadata maintained increases, an ever increasing amount of cache storage and processing capacity is dedicated to metadata, to the exclusion of other types of data. In addition, because cache storage is volatile (data stored in cache will be lost in the event of a power loss), some conventional computing systems save metadata that has been modified in cache into separate, battery-backed-up, non-volatile storage units (NVS) for recovery purposes. Such implementations add additional costs and overhead by consuming processor and memory resources to maintain and update the metadata in NVS
To conserve NVS capacity, some computing systems will not back-up metadata in NVS. The problem with not providing an NVS backup is that microcode errors, power loss, and other error conditions may cause some or all of the metadata stored in cache to become corrupted or lost. In such case, the storage controller must rebuild the metadata from the actual data in the DASD. This process of recovering lost metadata can be time-consuming, as metadata often represents thousands of customer tracks. In conventional computing systems when modified metadata is not backed-up into NVS, corrupted metadata must be invalidated while the controller is off-line from the host. Then, the metadata is rebuilt in a piecemeal process when its associated customer data is staged into cache for other purposes. As will be appreciated, the, off-line process degrades normal data processing operations.
There thus is a need in the art for an improved method and system for performing a more efficient recovery following a metadata error.